A comparison between usage‐based and citation‐based methods for recommending scholarly research articles
Andre N. Vellino · Proceedings of the American Society for Information Science and Technology · 2010
Abstract This study compares some of the behavioural characteristics of two recommender systems for scholarly articles in a digital library: a usage‐based recommender and an experimental citation‐based recommender. Experimental results show that article recommendations based only on usage data are slightly better at solving the perennial data‐sparsity problem that plagues collaborative filtering recommenders in digital libraries. However, citation‐based recommendations are more semantically diverse and have less in common with conventional search results than the usage‐based method. However both of these methods are complementary since most of the time if one recommender produces a list of recommendations the other does not.